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diff --git a/kaldi_io/src/kaldi/matrix/kaldi-matrix.h b/kaldi_io/src/kaldi/matrix/kaldi-matrix.h deleted file mode 100644 index e6829e0..0000000 --- a/kaldi_io/src/kaldi/matrix/kaldi-matrix.h +++ /dev/null @@ -1,983 +0,0 @@ -// matrix/kaldi-matrix.h - -// Copyright 2009-2011 Ondrej Glembek; Microsoft Corporation; Lukas Burget; -// Saarland University; Petr Schwarz; Yanmin Qian; -// Karel Vesely; Go Vivace Inc.; Haihua Xu - -// See ../../COPYING for clarification regarding multiple authors -// -// Licensed under the Apache License, Version 2.0 (the "License"); -// you may not use this file except in compliance with the License. -// You may obtain a copy of the License at -// -// http://www.apache.org/licenses/LICENSE-2.0 -// -// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY -// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED -// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE, -// MERCHANTABLITY OR NON-INFRINGEMENT. -// See the Apache 2 License for the specific language governing permissions and -// limitations under the License. - -#ifndef KALDI_MATRIX_KALDI_MATRIX_H_ -#define KALDI_MATRIX_KALDI_MATRIX_H_ 1 - -#include "matrix/matrix-common.h" - -namespace kaldi { - -/// @{ \addtogroup matrix_funcs_scalar - -/// We need to declare this here as it will be a friend function. -/// tr(A B), or tr(A B^T). -template<typename Real> -Real TraceMatMat(const MatrixBase<Real> &A, const MatrixBase<Real> &B, - MatrixTransposeType trans = kNoTrans); -/// @} - -/// \addtogroup matrix_group -/// @{ - -/// Base class which provides matrix operations not involving resizing -/// or allocation. Classes Matrix and SubMatrix inherit from it and take care -/// of allocation and resizing. -template<typename Real> -class MatrixBase { - public: - // so this child can access protected members of other instances. - friend class Matrix<Real>; - // friend declarations for CUDA matrices (see ../cudamatrix/) - friend class CuMatrixBase<Real>; - friend class CuMatrix<Real>; - friend class CuSubMatrix<Real>; - friend class CuPackedMatrix<Real>; - - friend class PackedMatrix<Real>; - - /// Returns number of rows (or zero for emtpy matrix). - inline MatrixIndexT NumRows() const { return num_rows_; } - - /// Returns number of columns (or zero for emtpy matrix). - inline MatrixIndexT NumCols() const { return num_cols_; } - - /// Stride (distance in memory between each row). Will be >= NumCols. - inline MatrixIndexT Stride() const { return stride_; } - - /// Returns size in bytes of the data held by the matrix. - size_t SizeInBytes() const { - return static_cast<size_t>(num_rows_) * static_cast<size_t>(stride_) * - sizeof(Real); - } - - /// Gives pointer to raw data (const). - inline const Real* Data() const { - return data_; - } - - /// Gives pointer to raw data (non-const). - inline Real* Data() { return data_; } - - /// Returns pointer to data for one row (non-const) - inline Real* RowData(MatrixIndexT i) { - KALDI_ASSERT(static_cast<UnsignedMatrixIndexT>(i) < - static_cast<UnsignedMatrixIndexT>(num_rows_)); - return data_ + i * stride_; - } - - /// Returns pointer to data for one row (const) - inline const Real* RowData(MatrixIndexT i) const { - KALDI_ASSERT(static_cast<UnsignedMatrixIndexT>(i) < - static_cast<UnsignedMatrixIndexT>(num_rows_)); - return data_ + i * stride_; - } - - /// Indexing operator, non-const - /// (only checks sizes if compiled with -DKALDI_PARANOID) - inline Real& operator() (MatrixIndexT r, MatrixIndexT c) { - KALDI_PARANOID_ASSERT(static_cast<UnsignedMatrixIndexT>(r) < - static_cast<UnsignedMatrixIndexT>(num_rows_) && - static_cast<UnsignedMatrixIndexT>(c) < - static_cast<UnsignedMatrixIndexT>(num_cols_)); - return *(data_ + r * stride_ + c); - } - /// Indexing operator, provided for ease of debugging (gdb doesn't work - /// with parenthesis operator). - Real &Index (MatrixIndexT r, MatrixIndexT c) { return (*this)(r, c); } - - /// Indexing operator, const - /// (only checks sizes if compiled with -DKALDI_PARANOID) - inline const Real operator() (MatrixIndexT r, MatrixIndexT c) const { - KALDI_PARANOID_ASSERT(static_cast<UnsignedMatrixIndexT>(r) < - static_cast<UnsignedMatrixIndexT>(num_rows_) && - static_cast<UnsignedMatrixIndexT>(c) < - static_cast<UnsignedMatrixIndexT>(num_cols_)); - return *(data_ + r * stride_ + c); - } - - /* Basic setting-to-special values functions. */ - - /// Sets matrix to zero. - void SetZero(); - /// Sets all elements to a specific value. - void Set(Real); - /// Sets to zero, except ones along diagonal [for non-square matrices too] - void SetUnit(); - /// Sets to random values of a normal distribution - void SetRandn(); - /// Sets to numbers uniformly distributed on (0, 1) - void SetRandUniform(); - - /* Copying functions. These do not resize the matrix! */ - - - /// Copy given matrix. (no resize is done). - template<typename OtherReal> - void CopyFromMat(const MatrixBase<OtherReal> & M, - MatrixTransposeType trans = kNoTrans); - - /// Copy from compressed matrix. - void CopyFromMat(const CompressedMatrix &M); - - /// Copy given spmatrix. (no resize is done). - template<typename OtherReal> - void CopyFromSp(const SpMatrix<OtherReal> &M); - - /// Copy given tpmatrix. (no resize is done). - template<typename OtherReal> - void CopyFromTp(const TpMatrix<OtherReal> &M, - MatrixTransposeType trans = kNoTrans); - - /// Copy from CUDA matrix. Implemented in ../cudamatrix/cu-matrix.h - template<typename OtherReal> - void CopyFromMat(const CuMatrixBase<OtherReal> &M, - MatrixTransposeType trans = kNoTrans); - - /// Inverse of vec() operator. Copies vector into matrix, row-by-row. - /// Note that rv.Dim() must either equal NumRows()*NumCols() or - /// NumCols()-- this has two modes of operation. - void CopyRowsFromVec(const VectorBase<Real> &v); - - /// This version of CopyRowsFromVec is implemented in ../cudamatrix/cu-vector.cc - void CopyRowsFromVec(const CuVectorBase<Real> &v); - - template<typename OtherReal> - void CopyRowsFromVec(const VectorBase<OtherReal> &v); - - /// Copies vector into matrix, column-by-column. - /// Note that rv.Dim() must either equal NumRows()*NumCols() or NumRows(); - /// this has two modes of operation. - void CopyColsFromVec(const VectorBase<Real> &v); - - /// Copy vector into specific column of matrix. - void CopyColFromVec(const VectorBase<Real> &v, const MatrixIndexT col); - /// Copy vector into specific row of matrix. - void CopyRowFromVec(const VectorBase<Real> &v, const MatrixIndexT row); - /// Copy vector into diagonal of matrix. - void CopyDiagFromVec(const VectorBase<Real> &v); - - /* Accessing of sub-parts of the matrix. */ - - /// Return specific row of matrix [const]. - inline const SubVector<Real> Row(MatrixIndexT i) const { - KALDI_ASSERT(static_cast<UnsignedMatrixIndexT>(i) < - static_cast<UnsignedMatrixIndexT>(num_rows_)); - return SubVector<Real>(data_ + (i * stride_), NumCols()); - } - - /// Return specific row of matrix. - inline SubVector<Real> Row(MatrixIndexT i) { - KALDI_ASSERT(static_cast<UnsignedMatrixIndexT>(i) < - static_cast<UnsignedMatrixIndexT>(num_rows_)); - return SubVector<Real>(data_ + (i * stride_), NumCols()); - } - - /// Return a sub-part of matrix. - inline SubMatrix<Real> Range(const MatrixIndexT row_offset, - const MatrixIndexT num_rows, - const MatrixIndexT col_offset, - const MatrixIndexT num_cols) const { - return SubMatrix<Real>(*this, row_offset, num_rows, - col_offset, num_cols); - } - inline SubMatrix<Real> RowRange(const MatrixIndexT row_offset, - const MatrixIndexT num_rows) const { - return SubMatrix<Real>(*this, row_offset, num_rows, 0, num_cols_); - } - inline SubMatrix<Real> ColRange(const MatrixIndexT col_offset, - const MatrixIndexT num_cols) const { - return SubMatrix<Real>(*this, 0, num_rows_, col_offset, num_cols); - } - - /* Various special functions. */ - /// Returns sum of all elements in matrix. - Real Sum() const; - /// Returns trace of matrix. - Real Trace(bool check_square = true) const; - // If check_square = true, will crash if matrix is not square. - - /// Returns maximum element of matrix. - Real Max() const; - /// Returns minimum element of matrix. - Real Min() const; - - /// Element by element multiplication with a given matrix. - void MulElements(const MatrixBase<Real> &A); - - /// Divide each element by the corresponding element of a given matrix. - void DivElements(const MatrixBase<Real> &A); - - /// Multiply each element with a scalar value. - void Scale(Real alpha); - - /// Set, element-by-element, *this = max(*this, A) - void Max(const MatrixBase<Real> &A); - - /// Equivalent to (*this) = (*this) * diag(scale). Scaling - /// each column by a scalar taken from that dimension of the vector. - void MulColsVec(const VectorBase<Real> &scale); - - /// Equivalent to (*this) = diag(scale) * (*this). Scaling - /// each row by a scalar taken from that dimension of the vector. - void MulRowsVec(const VectorBase<Real> &scale); - - /// Divide each row into src.NumCols() equal groups, and then scale i'th row's - /// j'th group of elements by src(i, j). Requires src.NumRows() == - /// this->NumRows() and this->NumCols() % src.NumCols() == 0. - void MulRowsGroupMat(const MatrixBase<Real> &src); - - /// Returns logdet of matrix. - Real LogDet(Real *det_sign = NULL) const; - - /// matrix inverse. - /// if inverse_needed = false, will fill matrix with garbage. - /// (only useful if logdet wanted). - void Invert(Real *log_det = NULL, Real *det_sign = NULL, - bool inverse_needed = true); - /// matrix inverse [double]. - /// if inverse_needed = false, will fill matrix with garbage - /// (only useful if logdet wanted). - /// Does inversion in double precision even if matrix was not double. - void InvertDouble(Real *LogDet = NULL, Real *det_sign = NULL, - bool inverse_needed = true); - - /// Inverts all the elements of the matrix - void InvertElements(); - - /// Transpose the matrix. This one is only - /// applicable to square matrices (the one in the - /// Matrix child class works also for non-square. - void Transpose(); - - /// Copies column r from column indices[r] of src. - /// As a special case, if indexes[i] == -1, sets column i to zero - /// indices.size() must equal this->NumCols(), - /// all elements of "reorder" must be in [-1, src.NumCols()-1], - /// and src.NumRows() must equal this.NumRows() - void CopyCols(const MatrixBase<Real> &src, - const std::vector<MatrixIndexT> &indices); - - /// Copies row r from row indices[r] of src. - /// As a special case, if indexes[i] == -1, sets row i to zero - /// "reorder".size() must equal this->NumRows(), - /// all elements of "reorder" must be in [-1, src.NumRows()-1], - /// and src.NumCols() must equal this.NumCols() - void CopyRows(const MatrixBase<Real> &src, - const std::vector<MatrixIndexT> &indices); - - /// Applies floor to all matrix elements - void ApplyFloor(Real floor_val); - - /// Applies floor to all matrix elements - void ApplyCeiling(Real ceiling_val); - - /// Calculates log of all the matrix elemnts - void ApplyLog(); - - /// Exponentiate each of the elements. - void ApplyExp(); - - /// Applies power to all matrix elements - void ApplyPow(Real power); - - /// Apply power to the absolute value of each element. - /// Include the sign of the input element if include_sign == true. - /// If the power is negative and the input to the power is zero, - /// The output will be set zero. - void ApplyPowAbs(Real power, bool include_sign=false); - - /// Applies the Heaviside step function (x > 0 ? 1 : 0) to all matrix elements - /// Note: in general you can make different choices for x = 0, but for now - /// please leave it as it (i.e. returning zero) because it affects the - /// RectifiedLinearComponent in the neural net code. - void ApplyHeaviside(); - - /// Eigenvalue Decomposition of a square NxN matrix into the form (*this) = P D - /// P^{-1}. Be careful: the relationship of D to the eigenvalues we output is - /// slightly complicated, due to the need for P to be real. In the symmetric - /// case D is diagonal and real, but in - /// the non-symmetric case there may be complex-conjugate pairs of eigenvalues. - /// In this case, for the equation (*this) = P D P^{-1} to hold, D must actually - /// be block diagonal, with 2x2 blocks corresponding to any such pairs. If a - /// pair is lambda +- i*mu, D will have a corresponding 2x2 block - /// [lambda, mu; -mu, lambda]. - /// Note that if the input matrix (*this) is non-invertible, P may not be invertible - /// so in this case instead of the equation (*this) = P D P^{-1} holding, we have - /// instead (*this) P = P D. - /// - /// The non-member function CreateEigenvalueMatrix creates D from eigs_real and eigs_imag. - void Eig(MatrixBase<Real> *P, - VectorBase<Real> *eigs_real, - VectorBase<Real> *eigs_imag) const; - - /// The Power method attempts to take the matrix to a power using a method that - /// works in general for fractional and negative powers. The input matrix must - /// be invertible and have reasonable condition (or we don't guarantee the - /// results. The method is based on the eigenvalue decomposition. It will - /// return false and leave the matrix unchanged, if at entry the matrix had - /// real negative eigenvalues (or if it had zero eigenvalues and the power was - /// negative). - bool Power(Real pow); - - /** Singular value decomposition - Major limitations: - For nonsquare matrices, we assume m>=n (NumRows >= NumCols), and we return - the "skinny" Svd, i.e. the matrix in the middle is diagonal, and the - one on the left is rectangular. - - In Svd, *this = U*diag(S)*Vt. - Null pointers for U and/or Vt at input mean we do not want that output. We - expect that S.Dim() == m, U is either NULL or m by n, - and v is either NULL or n by n. - The singular values are not sorted (use SortSvd for that). */ - void DestructiveSvd(VectorBase<Real> *s, MatrixBase<Real> *U, - MatrixBase<Real> *Vt); // Destroys calling matrix. - - /// Compute SVD (*this) = U diag(s) Vt. Note that the V in the call is already - /// transposed; the normal formulation is U diag(s) V^T. - /// Null pointers for U or V mean we don't want that output (this saves - /// compute). The singular values are not sorted (use SortSvd for that). - void Svd(VectorBase<Real> *s, MatrixBase<Real> *U, - MatrixBase<Real> *Vt) const; - /// Compute SVD but only retain the singular values. - void Svd(VectorBase<Real> *s) const { Svd(s, NULL, NULL); } - - - /// Returns smallest singular value. - Real MinSingularValue() const { - Vector<Real> tmp(std::min(NumRows(), NumCols())); - Svd(&tmp); - return tmp.Min(); - } - - void TestUninitialized() const; // This function is designed so that if any element - // if the matrix is uninitialized memory, valgrind will complain. - - /// Returns condition number by computing Svd. Works even if cols > rows. - /// Returns infinity if all singular values are zero. - Real Cond() const; - - /// Returns true if matrix is Symmetric. - bool IsSymmetric(Real cutoff = 1.0e-05) const; // replace magic number - - /// Returns true if matrix is Diagonal. - bool IsDiagonal(Real cutoff = 1.0e-05) const; // replace magic number - - /// Returns true if the matrix is all zeros, except for ones on diagonal. (it - /// does not have to be square). More specifically, this function returns - /// false if for any i, j, (*this)(i, j) differs by more than cutoff from the - /// expression (i == j ? 1 : 0). - bool IsUnit(Real cutoff = 1.0e-05) const; // replace magic number - - /// Returns true if matrix is all zeros. - bool IsZero(Real cutoff = 1.0e-05) const; // replace magic number - - /// Frobenius norm, which is the sqrt of sum of square elements. Same as Schatten 2-norm, - /// or just "2-norm". - Real FrobeniusNorm() const; - - /// Returns true if ((*this)-other).FrobeniusNorm() - /// <= tol * (*this).FrobeniusNorm(). - bool ApproxEqual(const MatrixBase<Real> &other, float tol = 0.01) const; - - /// Tests for exact equality. It's usually preferable to use ApproxEqual. - bool Equal(const MatrixBase<Real> &other) const; - - /// largest absolute value. - Real LargestAbsElem() const; // largest absolute value. - - /// Returns log(sum(exp())) without exp overflow - /// If prune > 0.0, it uses a pruning beam, discarding - /// terms less than (max - prune). Note: in future - /// we may change this so that if prune = 0.0, it takes - /// the max, so use -1 if you don't want to prune. - Real LogSumExp(Real prune = -1.0) const; - - /// Apply soft-max to the collection of all elements of the - /// matrix and return normalizer (log sum of exponentials). - Real ApplySoftMax(); - - /// Set each element to the sigmoid of the corresponding element of "src". - void Sigmoid(const MatrixBase<Real> &src); - - /// Set each element to y = log(1 + exp(x)) - void SoftHinge(const MatrixBase<Real> &src); - - /// Apply the function y(i) = (sum_{j = i*G}^{(i+1)*G-1} x_j^(power))^(1 / p). - /// Requires src.NumRows() == this->NumRows() and src.NumCols() % this->NumCols() == 0. - void GroupPnorm(const MatrixBase<Real> &src, Real power); - - - /// Calculate derivatives for the GroupPnorm function above... - /// if "input" is the input to the GroupPnorm function above (i.e. the "src" variable), - /// and "output" is the result of the computation (i.e. the "this" of that function - /// call), and *this has the same dimension as "input", then it sets each element - /// of *this to the derivative d(output-elem)/d(input-elem) for each element of "input", where - /// "output-elem" is whichever element of output depends on that input element. - void GroupPnormDeriv(const MatrixBase<Real> &input, const MatrixBase<Real> &output, - Real power); - - - /// Set each element to the tanh of the corresponding element of "src". - void Tanh(const MatrixBase<Real> &src); - - // Function used in backpropagating derivatives of the sigmoid function: - // element-by-element, set *this = diff * value * (1.0 - value). - void DiffSigmoid(const MatrixBase<Real> &value, - const MatrixBase<Real> &diff); - - // Function used in backpropagating derivatives of the tanh function: - // element-by-element, set *this = diff * (1.0 - value^2). - void DiffTanh(const MatrixBase<Real> &value, - const MatrixBase<Real> &diff); - - /** Uses Svd to compute the eigenvalue decomposition of a symmetric positive - * semi-definite matrix: (*this) = rP * diag(rS) * rP^T, with rP an - * orthogonal matrix so rP^{-1} = rP^T. Throws exception if input was not - * positive semi-definite (check_thresh controls how stringent the check is; - * set it to 2 to ensure it won't ever complain, but it will zero out negative - * dimensions in your matrix. - */ - void SymPosSemiDefEig(VectorBase<Real> *s, MatrixBase<Real> *P, - Real check_thresh = 0.001); - - friend Real kaldi::TraceMatMat<Real>(const MatrixBase<Real> &A, - const MatrixBase<Real> &B, MatrixTransposeType trans); // tr (A B) - - // so it can get around const restrictions on the pointer to data_. - friend class SubMatrix<Real>; - - /// Add a scalar to each element - void Add(const Real alpha); - - /// Add a scalar to each diagonal element. - void AddToDiag(const Real alpha); - - /// *this += alpha * a * b^T - template<typename OtherReal> - void AddVecVec(const Real alpha, const VectorBase<OtherReal> &a, - const VectorBase<OtherReal> &b); - - /// [each row of *this] += alpha * v - template<typename OtherReal> - void AddVecToRows(const Real alpha, const VectorBase<OtherReal> &v); - - /// [each col of *this] += alpha * v - template<typename OtherReal> - void AddVecToCols(const Real alpha, const VectorBase<OtherReal> &v); - - /// *this += alpha * M [or M^T] - void AddMat(const Real alpha, const MatrixBase<Real> &M, - MatrixTransposeType transA = kNoTrans); - - /// *this = beta * *this + alpha * M M^T, for symmetric matrices. It only - /// updates the lower triangle of *this. It will leave the matrix asymmetric; - /// if you need it symmetric as a regular matrix, do CopyLowerToUpper(). - void SymAddMat2(const Real alpha, const MatrixBase<Real> &M, - MatrixTransposeType transA, Real beta); - - /// *this = beta * *this + alpha * diag(v) * M [or M^T]. - /// The same as adding M but scaling each row M_i by v(i). - void AddDiagVecMat(const Real alpha, VectorBase<Real> &v, - const MatrixBase<Real> &M, MatrixTransposeType transM, - Real beta = 1.0); - - /// *this = beta * *this + alpha * M [or M^T] * diag(v) - /// The same as adding M but scaling each column M_j by v(j). - void AddMatDiagVec(const Real alpha, - const MatrixBase<Real> &M, MatrixTransposeType transM, - VectorBase<Real> &v, - Real beta = 1.0); - - /// *this = beta * *this + alpha * A .* B (.* element by element multiplication) - void AddMatMatElements(const Real alpha, - const MatrixBase<Real>& A, - const MatrixBase<Real>& B, - const Real beta); - - /// *this += alpha * S - template<typename OtherReal> - void AddSp(const Real alpha, const SpMatrix<OtherReal> &S); - - void AddMatMat(const Real alpha, - const MatrixBase<Real>& A, MatrixTransposeType transA, - const MatrixBase<Real>& B, MatrixTransposeType transB, - const Real beta); - - /// *this = a * b / c (by element; when c = 0, *this = a) - void AddMatMatDivMat(const MatrixBase<Real>& A, - const MatrixBase<Real>& B, - const MatrixBase<Real>& C); - - /// A version of AddMatMat specialized for when the second argument - /// contains a lot of zeroes. - void AddMatSmat(const Real alpha, - const MatrixBase<Real>& A, MatrixTransposeType transA, - const MatrixBase<Real>& B, MatrixTransposeType transB, - const Real beta); - - /// A version of AddMatMat specialized for when the first argument - /// contains a lot of zeroes. - void AddSmatMat(const Real alpha, - const MatrixBase<Real>& A, MatrixTransposeType transA, - const MatrixBase<Real>& B, MatrixTransposeType transB, - const Real beta); - - /// this <-- beta*this + alpha*A*B*C. - void AddMatMatMat(const Real alpha, - const MatrixBase<Real>& A, MatrixTransposeType transA, - const MatrixBase<Real>& B, MatrixTransposeType transB, - const MatrixBase<Real>& C, MatrixTransposeType transC, - const Real beta); - - /// this <-- beta*this + alpha*SpA*B. - // This and the routines below are really - // stubs that need to be made more efficient. - void AddSpMat(const Real alpha, - const SpMatrix<Real>& A, - const MatrixBase<Real>& B, MatrixTransposeType transB, - const Real beta) { - Matrix<Real> M(A); - return AddMatMat(alpha, M, kNoTrans, B, transB, beta); - } - /// this <-- beta*this + alpha*A*B. - void AddTpMat(const Real alpha, - const TpMatrix<Real>& A, MatrixTransposeType transA, - const MatrixBase<Real>& B, MatrixTransposeType transB, - const Real beta) { - Matrix<Real> M(A); - return AddMatMat(alpha, M, transA, B, transB, beta); - } - /// this <-- beta*this + alpha*A*B. - void AddMatSp(const Real alpha, - const MatrixBase<Real>& A, MatrixTransposeType transA, - const SpMatrix<Real>& B, - const Real beta) { - Matrix<Real> M(B); - return AddMatMat(alpha, A, transA, M, kNoTrans, beta); - } - /// this <-- beta*this + alpha*A*B*C. - void AddSpMatSp(const Real alpha, - const SpMatrix<Real> &A, - const MatrixBase<Real>& B, MatrixTransposeType transB, - const SpMatrix<Real>& C, - const Real beta) { - Matrix<Real> M(A), N(C); - return AddMatMatMat(alpha, M, kNoTrans, B, transB, N, kNoTrans, beta); - } - /// this <-- beta*this + alpha*A*B. - void AddMatTp(const Real alpha, - const MatrixBase<Real>& A, MatrixTransposeType transA, - const TpMatrix<Real>& B, MatrixTransposeType transB, - const Real beta) { - Matrix<Real> M(B); - return AddMatMat(alpha, A, transA, M, transB, beta); - } - - /// this <-- beta*this + alpha*A*B. - void AddTpTp(const Real alpha, - const TpMatrix<Real>& A, MatrixTransposeType transA, - const TpMatrix<Real>& B, MatrixTransposeType transB, - const Real beta) { - Matrix<Real> M(A), N(B); - return AddMatMat(alpha, M, transA, N, transB, beta); - } - - /// this <-- beta*this + alpha*A*B. - // This one is more efficient, not like the others above. - void AddSpSp(const Real alpha, - const SpMatrix<Real>& A, const SpMatrix<Real>& B, - const Real beta); - - /// Copy lower triangle to upper triangle (symmetrize) - void CopyLowerToUpper(); - - /// Copy upper triangle to lower triangle (symmetrize) - void CopyUpperToLower(); - - /// This function orthogonalizes the rows of a matrix using the Gram-Schmidt - /// process. It is only applicable if NumRows() <= NumCols(). It will use - /// random number generation to fill in rows with something nonzero, in cases - /// where the original matrix was of deficient row rank. - void OrthogonalizeRows(); - - /// stream read. - /// Use instead of stream<<*this, if you want to add to existing contents. - // Will throw exception on failure. - void Read(std::istream & in, bool binary, bool add = false); - /// write to stream. - void Write(std::ostream & out, bool binary) const; - - // Below is internal methods for Svd, user does not have to know about this. -#if !defined(HAVE_ATLAS) && !defined(USE_KALDI_SVD) - // protected: - // Should be protected but used directly in testing routine. - // destroys *this! - void LapackGesvd(VectorBase<Real> *s, MatrixBase<Real> *U, - MatrixBase<Real> *Vt); -#else - protected: - // destroys *this! - bool JamaSvd(VectorBase<Real> *s, MatrixBase<Real> *U, - MatrixBase<Real> *V); - -#endif - protected: - - /// Initializer, callable only from child. - explicit MatrixBase(Real *data, MatrixIndexT cols, MatrixIndexT rows, MatrixIndexT stride) : - data_(data), num_cols_(cols), num_rows_(rows), stride_(stride) { - KALDI_ASSERT_IS_FLOATING_TYPE(Real); - } - - /// Initializer, callable only from child. - /// Empty initializer, for un-initialized matrix. - explicit MatrixBase(): data_(NULL) { - KALDI_ASSERT_IS_FLOATING_TYPE(Real); - } - - // Make sure pointers to MatrixBase cannot be deleted. - ~MatrixBase() { } - - /// A workaround that allows SubMatrix to get a pointer to non-const data - /// for const Matrix. Unfortunately C++ does not allow us to declare a - /// "public const" inheritance or anything like that, so it would require - /// a lot of work to make the SubMatrix class totally const-correct-- - /// we would have to override many of the Matrix functions. - inline Real* Data_workaround() const { - return data_; - } - - /// data memory area - Real* data_; - - /// these atributes store the real matrix size as it is stored in memory - /// including memalignment - MatrixIndexT num_cols_; /// < Number of columns - MatrixIndexT num_rows_; /// < Number of rows - /** True number of columns for the internal matrix. This number may differ - * from num_cols_ as memory alignment might be used. */ - MatrixIndexT stride_; - private: - KALDI_DISALLOW_COPY_AND_ASSIGN(MatrixBase); -}; - -/// A class for storing matrices. -template<typename Real> -class Matrix : public MatrixBase<Real> { - public: - - /// Empty constructor. - Matrix(); - - /// Basic constructor. Sets to zero by default. - /// if set_zero == false, memory contents are undefined. - Matrix(const MatrixIndexT r, const MatrixIndexT c, - MatrixResizeType resize_type = kSetZero): - MatrixBase<Real>() { Resize(r, c, resize_type); } - - /// Copy constructor from CUDA matrix - /// This is defined in ../cudamatrix/cu-matrix.h - template<typename OtherReal> - explicit Matrix(const CuMatrixBase<OtherReal> &cu, - MatrixTransposeType trans = kNoTrans); - - - /// Swaps the contents of *this and *other. Shallow swap. - void Swap(Matrix<Real> *other); - - /// Defined in ../cudamatrix/cu-matrix.cc - void Swap(CuMatrix<Real> *mat); - - /// Constructor from any MatrixBase. Can also copy with transpose. - /// Allocates new memory. - explicit Matrix(const MatrixBase<Real> & M, - MatrixTransposeType trans = kNoTrans); - - /// Same as above, but need to avoid default copy constructor. - Matrix(const Matrix<Real> & M); // (cannot make explicit) - - /// Copy constructor: as above, but from another type. - template<typename OtherReal> - explicit Matrix(const MatrixBase<OtherReal> & M, - MatrixTransposeType trans = kNoTrans); - - /// Copy constructor taking SpMatrix... - /// It is symmetric, so no option for transpose, and NumRows == Cols - template<typename OtherReal> - explicit Matrix(const SpMatrix<OtherReal> & M) : MatrixBase<Real>() { - Resize(M.NumRows(), M.NumRows(), kUndefined); - this->CopyFromSp(M); - } - - /// Constructor from CompressedMatrix - explicit Matrix(const CompressedMatrix &C); - - /// Copy constructor taking TpMatrix... - template <typename OtherReal> - explicit Matrix(const TpMatrix<OtherReal> & M, - MatrixTransposeType trans = kNoTrans) : MatrixBase<Real>() { - if (trans == kNoTrans) { - Resize(M.NumRows(), M.NumCols(), kUndefined); - this->CopyFromTp(M); - } else { - Resize(M.NumCols(), M.NumRows(), kUndefined); - this->CopyFromTp(M, kTrans); - } - } - - /// read from stream. - // Unlike one in base, allows resizing. - void Read(std::istream & in, bool binary, bool add = false); - - /// Remove a specified row. - void RemoveRow(MatrixIndexT i); - - /// Transpose the matrix. Works for non-square - /// matrices as well as square ones. - void Transpose(); - - /// Distructor to free matrices. - ~Matrix() { Destroy(); } - - /// Sets matrix to a specified size (zero is OK as long as both r and c are - /// zero). The value of the new data depends on resize_type: - /// -if kSetZero, the new data will be zero - /// -if kUndefined, the new data will be undefined - /// -if kCopyData, the new data will be the same as the old data in any - /// shared positions, and zero elsewhere. - /// This function takes time proportional to the number of data elements. - void Resize(const MatrixIndexT r, - const MatrixIndexT c, - MatrixResizeType resize_type = kSetZero); - - /// Assignment operator that takes MatrixBase. - Matrix<Real> &operator = (const MatrixBase<Real> &other) { - if (MatrixBase<Real>::NumRows() != other.NumRows() || - MatrixBase<Real>::NumCols() != other.NumCols()) - Resize(other.NumRows(), other.NumCols(), kUndefined); - MatrixBase<Real>::CopyFromMat(other); - return *this; - } - - /// Assignment operator. Needed for inclusion in std::vector. - Matrix<Real> &operator = (const Matrix<Real> &other) { - if (MatrixBase<Real>::NumRows() != other.NumRows() || - MatrixBase<Real>::NumCols() != other.NumCols()) - Resize(other.NumRows(), other.NumCols(), kUndefined); - MatrixBase<Real>::CopyFromMat(other); - return *this; - } - - - private: - /// Deallocates memory and sets to empty matrix (dimension 0, 0). - void Destroy(); - - /// Init assumes the current class contents are invalid (i.e. junk or have - /// already been freed), and it sets the matrix to newly allocated memory with - /// the specified number of rows and columns. r == c == 0 is acceptable. The data - /// memory contents will be undefined. - void Init(const MatrixIndexT r, - const MatrixIndexT c); - -}; -/// @} end "addtogroup matrix_group" - -/// \addtogroup matrix_funcs_io -/// @{ - -/// A structure containing the HTK header. -/// [TODO: change the style of the variables to Kaldi-compliant] -struct HtkHeader { - /// Number of samples. - int32 mNSamples; - /// Sample period. - int32 mSamplePeriod; - /// Sample size - int16 mSampleSize; - /// Sample kind. - uint16 mSampleKind; -}; - -// Read HTK formatted features from file into matrix. -template<typename Real> -bool ReadHtk(std::istream &is, Matrix<Real> *M, HtkHeader *header_ptr); - -// Write (HTK format) features to file from matrix. -template<typename Real> -bool WriteHtk(std::ostream &os, const MatrixBase<Real> &M, HtkHeader htk_hdr); - -// Write (CMUSphinx format) features to file from matrix. -template<typename Real> -bool WriteSphinx(std::ostream &os, const MatrixBase<Real> &M); - -/// @} end of "addtogroup matrix_funcs_io" - -/** - Sub-matrix representation. - Can work with sub-parts of a matrix using this class. - Note that SubMatrix is not very const-correct-- it allows you to - change the contents of a const Matrix. Be careful! -*/ - -template<typename Real> -class SubMatrix : public MatrixBase<Real> { - public: - // Initialize a SubMatrix from part of a matrix; this is - // a bit like A(b:c, d:e) in Matlab. - // This initializer is against the proper semantics of "const", since - // SubMatrix can change its contents. It would be hard to implement - // a "const-safe" version of this class. - SubMatrix(const MatrixBase<Real>& T, - const MatrixIndexT ro, // row offset, 0 < ro < NumRows() - const MatrixIndexT r, // number of rows, r > 0 - const MatrixIndexT co, // column offset, 0 < co < NumCols() - const MatrixIndexT c); // number of columns, c > 0 - - // This initializer is mostly intended for use in CuMatrix and related - // classes. Be careful! - SubMatrix(Real *data, - MatrixIndexT num_rows, - MatrixIndexT num_cols, - MatrixIndexT stride); - - ~SubMatrix<Real>() {} - - /// This type of constructor is needed for Range() to work [in Matrix base - /// class]. Cannot make it explicit. - SubMatrix<Real> (const SubMatrix &other): - MatrixBase<Real> (other.data_, other.num_cols_, other.num_rows_, - other.stride_) {} - - private: - /// Disallow assignment. - SubMatrix<Real> &operator = (const SubMatrix<Real> &other); -}; -/// @} End of "addtogroup matrix_funcs_io". - -/// \addtogroup matrix_funcs_scalar -/// @{ - -// Some declarations. These are traces of products. - - -template<typename Real> -bool ApproxEqual(const MatrixBase<Real> &A, - const MatrixBase<Real> &B, |